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A Hybrid ACO-ACM Based Approach for Multi-cell Image Segmentation

机译:基于混合ACO-ACM的多细胞图像分割方法

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In this paper, a hybrid multi-cell image segmentation approach is proposed, based on the combination of active contour model (ACM) and ant colony optimization (ACO), for multi-cell image segmentation. This novel image segmentation algorithm integrates the characteristics of ACM model into the ACO with tractable and well defined energy and heuristic functions. Consequently, the problem of cell image segmentation is actually converted to search for the marks of cell contours by group of ants. Experiment results show that our proposed approach is more effective than several existing methods, and it is noted that our proposed approach is developed and implemented in Lab-VIEW as well with performance consistency.
机译:本文提出了一种基于主动轮廓模型(ACM)和蚁群优化(ACO)相结合的混合多细胞图像分割方法,用于多细胞图像分割。这种新颖的图像分割算法将ACM模型的特征整合到具有可控且定义明确的能量和启发式功能的ACO中。因此,细胞图像分割的问题实际上被转换为按蚂蚁群搜索细胞轮廓的标记。实验结果表明,我们提出的方法比几种现有方法更有效,并且注意到我们提出的方法是在Lab-VIEW中开发和实现的,并且具有性能一致性。

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